Jumptuit Unveils Forecasting Technology to Optimize Fleet Management
The cross-sector forecasting technology is also designed to to optimize fleet management, improve working conditions for supply-chain workers, and reduce carbon emissions

JAT’s cross-sector scenario forecasting aims to help drivers avoid dangerous or less than optimal driving conditions
Photo: Jumptuit
Jumptuit Autonomous Transit (JAT) has announced the market availability of its Commercial Fleet Vehicle Asset and Driver Management SaaS modules. JAT generates cross-sector scenario forecasts within standard commercial delivery timelines to optimize delivery performance metrics, including the efficient deployment of fleet vehicle assets and drivers.
JAT combines first-hand accounts, consensus views and sentiment, overhead livestream images and video, plus public and private data sources, synchronized by geolocation and time to create a comprehensive observation of an event, and forecast conditions for drivers en-route.
“In designing JAT, we developed a live multi-sector data streaming network generating cross-sector scenario forecasts with coverage for virtually all public roads and geolocations in the United States,” said Donald Leka, Founder, Chairman and Chief Executive Officer of Jumptuit, Inc. “JAT’s SaaS-based model for fleet vehicle assets and drivers provides flexible, easy to implement solutions for companies, reducing time to market and efficiently applying cross-sector scenario forecasting to virtually all public roads, with minimal capital investment.”
The Product
Jumptuit’s Software as a Service (SaaS) is offered in two modules - one to protect commercial fleet vehicle assets, and the other to protect commercial fleet drivers. JAT’s technology is designed to integrate with existing supply chain systems and operations.
JAT’s dynamic tracking of driving hours, mandatory rest breaks, and other working conditions works to assist companies with meeting Department of Transportation Driving Regulations for Fleet Management.
Module One: Commercial Fleet Vehicle Asset Management
Origin, Route and Destination Cross-Sector Forecasts
Optimal Scenario Departure Times and Routing Forecasts
Forecasted Events in Hazardous Accident Zones (HAZ)
Climate Emergency Alerts (CEA)
Climate Infrastructure Alerts (CIA)
Optimal Scenario Weather Advisory and Warning Forecasts
Optimal Scenario Carbon Emissions Forecasts
Optimal Scenario Energy Consumption Forecasts
Regulatory Compliance
Module Two: Commercial Fleet Driver Management
Individualized Risk Assessment Geolocation Forecasts for Public Health (e.g., airborne, contact and environmental, contamination)
Individualized Risk Assessment Geolocation Forecasts for Air Quality
Individualized Risk Assessment Geolocation Forecasts for Covid-19
Route Geolocation Proximity to Emergency Healthcare Services (e.g., hospitals, ICU bed availability)
Route Geolocation Safety Alerts (e.g., infrastructure failure, first responder activity)
Route Geolocation Charging Stations and Fuel Stops
Route Geolocation Driver Rest Stops and Overnight Accommodations
Regulatory Compliance
“Investing to improve driver working conditions is critical in addressing the challenges across the trucking industry and global supply chain,” said Leka. “JAT directly addresses the conditions that result in unpaid idle hours for drivers on the road, and put driver safety at risk.”
JAT’s cross-sector scenario forecasting aims to help drivers avoid dangerous or less than optimal driving conditions, including weather and route obstacles. JAT’s individualized health risk assessments help drivers to avoid potentially unsafe health and environmental conditions. JAT also alerts drivers to unexpected route events that could pose a personal safety risk, and proximity to emergency healthcare services.
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